Introduction
In this tutorial, we want to create a Stripplot. In order to do this, we use the stripplot() function of Seaborn.
Import Libraries
First, we import the following python modules:
import seaborn as sns
import matplotlib.pyplot as plt
Load Data
We would like to use a seaborn sample dataset. Let's load the "tips" dataset into python.
tips_df = sns.load_dataset("tips")
tips_df.head()
Stripplot
Stripplots are a special form of scatter plots and can be used to display the distribution of a numeric variable by a specific category.
By default, the points are randomly distributed along the categorical axis. This makes the points overlap less and clusters of data points become more visible.
Example 1: Plot one Variable
In our first example we want to visualize the given tips. In order to do this, we set the x parameter to "tip".
sns.stripplot(data=tips_df, x="tip")
plt.show()
Example 2: Plot two Variables
Now, let's display the distribution of the tips for each day. In addition to the x parameter, we use the y parameter and set it to "day".
sns.stripplot(data=tips_df, x="tip", y="day")
plt.show()
Example 3: Stripplot with Grouping
Now, let's highlight which tips were given at lunch and dinner. In order to do this, we use the hue parameter and set it to "time".
sns.stripplot(data=tips_df, x="tip", y="day", hue="time")
plt.show()
Example 4: Split Strips
Now, let's split the distribution for lunch and dinner into separate strips. In order to do this, we use the dodge parameter and set it to True.
sns.stripplot(data=tips_df, x="tip", y="day", hue ="time",
dodge=True)
plt.show()
Example 5: Change Style
Now, let's modify the styling of the plot. We use stars as markers and choose a different color palette.
sns.stripplot(data=tips_df, x="tip", y="day", hue ="time",
dodge=True, marker="*", size=22, alpha=0.3,
palette= "mako")
plt.show()
Conclusion
Congratulations! Now you are one step closer to become an AI Expert. You have seen that it is very easy to create a Stripplot. We can simply use the stripplot() function of Seaborn. Try it yourself!
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